#spatialpatterns — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #spatialpatterns, aggregated by home.social.
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Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
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https://doi.org/10.1038/s43247-026-03515-x <-- shared paper
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H/T @Peter Potapov | Researcher at the World Resources Institute (WRI)
“This paper is] a strong example of multifunctionality analysis applied to conservation planning. The study mapped six ecosystem functions, including carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity. [The author] combined satellite data, field soil sampling, and spatial modeling for this comprehensive analysis.
Two findings stand out.
1. Old-growth forests had the highest multifunctionality index of any land cover type.
2. 78.5% of the top multifunctionality hotspots fall outside the region's protected areas, even though PAs already cover more than 54% of the territory.
Together, these results make a clear case for expanding conservation of the remaining Intact Forest Landscapes and primary forests in Patagonia and elsewhere…”
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“Remote forest landscapes provide critical references for understanding ecosystem functions (EFs) under low anthropogenic pressure, yet their capacity to sustain multiple EFs simultaneously remains poorly understood. [They] assessed landscape multifunctionality in western Patagonia by integrating satellite indicators, field data, and spatial modeling. Six EFs (carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity) were mapped, and their spatial relationships and hotspot distribution within and outside protected areas (PAs) were analyzed. Old-growth and secondary forests showed the highest functional performance. Strong synergies (ρ ≥ 0.6) between carbon storage and nutrient availability covered >50% of the landscape, whereas strong trade-offs (ρ ≤ –0.6) were spatially limited ( < 6%). Notably, 78% of multifunctionality hotspots occurred outside PAs, indicating that high-functional-value areas extend beyond formal conservation boundaries. These findings reveal spatial mismatches between multifunctionality and protection status and provide a replicable framework for integrating multifunctionality into conservation planning under global change…”
#Patagonia #chile #aysen #coyhaique #landcover #mapping #spatial #spatialpatterns #spatiotemporal #spatialanalysis #forest #vegetation #oldgrowth #secondgrowth #shrubland #grassland #steppe #ecosystem #habitat #nutrients #water #hydrology #erosion #multifunctionality #multifunctionalityanalysis #protectedareas #landuse #conservationplanning #conservation #ecology #carbonstorage #nutrientavailability #waterregulation #erosioncontrol #habitatquality #ecologicalconnectivity #remotesensing #satellite #earthobservation #modeling -
Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
--
https://doi.org/10.1038/s43247-026-03515-x <-- shared paper
--
H/T @Peter Potapov | Researcher at the World Resources Institute (WRI)
“This paper is] a strong example of multifunctionality analysis applied to conservation planning. The study mapped six ecosystem functions, including carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity. [The author] combined satellite data, field soil sampling, and spatial modeling for this comprehensive analysis.
Two findings stand out.
1. Old-growth forests had the highest multifunctionality index of any land cover type.
2. 78.5% of the top multifunctionality hotspots fall outside the region's protected areas, even though PAs already cover more than 54% of the territory.
Together, these results make a clear case for expanding conservation of the remaining Intact Forest Landscapes and primary forests in Patagonia and elsewhere…”
--
“Remote forest landscapes provide critical references for understanding ecosystem functions (EFs) under low anthropogenic pressure, yet their capacity to sustain multiple EFs simultaneously remains poorly understood. [They] assessed landscape multifunctionality in western Patagonia by integrating satellite indicators, field data, and spatial modeling. Six EFs (carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity) were mapped, and their spatial relationships and hotspot distribution within and outside protected areas (PAs) were analyzed. Old-growth and secondary forests showed the highest functional performance. Strong synergies (ρ ≥ 0.6) between carbon storage and nutrient availability covered >50% of the landscape, whereas strong trade-offs (ρ ≤ –0.6) were spatially limited ( < 6%). Notably, 78% of multifunctionality hotspots occurred outside PAs, indicating that high-functional-value areas extend beyond formal conservation boundaries. These findings reveal spatial mismatches between multifunctionality and protection status and provide a replicable framework for integrating multifunctionality into conservation planning under global change…”
#Patagonia #chile #aysen #coyhaique #landcover #mapping #spatial #spatialpatterns #spatiotemporal #spatialanalysis #forest #vegetation #oldgrowth #secondgrowth #shrubland #grassland #steppe #ecosystem #habitat #nutrients #water #hydrology #erosion #multifunctionality #multifunctionalityanalysis #protectedareas #landuse #conservationplanning #conservation #ecology #carbonstorage #nutrientavailability #waterregulation #erosioncontrol #habitatquality #ecologicalconnectivity #remotesensing #satellite #earthobservation #modeling -
【🎉Latest accepted article】
#SpatialPatterns of #Non_structuralCarbohydrates in leaves and stems of #ChenopodioideaePlants along a desert transect in northwestern China -
It’s been 8 months since I started my MSCA-PF fellowship 🇩🇪
Read the latest blog post for updates on research, collaborations, and life in Münster.
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It’s been 8 months since I started my MSCA-PF fellowship 🇩🇪
Read the latest blog post for updates on research, collaborations, and life in Münster.
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🌌 Two blog posts about simulating spatial patterns with the kinetic Ising model.🌌
Part 1: https://buff.ly/3vbhvFJ
Part 2: https://buff.ly/3RNy1Ue -
🌌 Two blog posts about simulating spatial patterns with the kinetic Ising model.🌌
Part 1: https://buff.ly/3vbhvFJ
Part 2: https://buff.ly/3RNy1Ue -
🔥 The final blog post in my series on methods for comparing spatial patterns discusses its properties, applications, and extensions.🔥
Read it at https://buff.ly/40NozWQ
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🔥 The final blog post in my series on methods for comparing spatial patterns discusses its properties, applications, and extensions.🔥
Read it at https://buff.ly/40NozWQ
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Comparing spatial patterns blog post 5:
↔️ categorical raster data for arbitrary regions using #rstats↔️
Read it at https://buff.ly/4fgfYR4
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Comparing spatial patterns blog post 5:
↔️ categorical raster data for arbitrary regions using #rstats↔️
Read it at https://buff.ly/4fgfYR4
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Comparing spatial patterns blog post 4:
↔️ categorical raster data for overlapping regions using #rstats↔️
Read it at https://buff.ly/3NLNIJW.
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Comparing spatial patterns blog post 4:
↔️ categorical raster data for overlapping regions using #rstats↔️
Read it at https://buff.ly/3NLNIJW.
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Comparing spatial patterns blog post 3:
↔️ continuous raster data for arbitrary regions using #rstats↔️
Read it at https://buff.ly/48nkkU0.
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Comparing spatial patterns blog post 3:
↔️ continuous raster data for arbitrary regions using #rstats↔️
Read it at https://buff.ly/48nkkU0.
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Comparing spatial patterns blog post 2:
> continuous raster data for overlapping regions using #rstats <
Read it at https://buff.ly/4dZAIem.
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Comparing spatial patterns blog post 2:
> continuous raster data for overlapping regions using #rstats <
Read it at https://buff.ly/4dZAIem.
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🛰️ I just started publishing a blog post series on comparing spatial patterns in raster data.🛰️
Part one is about the motivation and the inventory of such methods.
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🛰️ I just started publishing a blog post series on comparing spatial patterns in raster data.🛰️
Part one is about the motivation and the inventory of such methods.
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🎥 My talk "Comparing spatial patterns in raster data using R" at #foss4ge2024 in Tartu is now available online.🎥
You can watch it at https://buff.ly/3XkYong.
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🎥 My talk "Comparing spatial patterns in raster data using R" at #foss4ge2024 in Tartu is now available online.🎥
You can watch it at https://buff.ly/3XkYong.
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✨ The GeoPAT 2 software allows the segmentation/regionalization of large spatial raster data.✨
Now, thanks to D G Rossiter, it can now be installed on MacOS.
You can find all of the instructions and other links at https://buff.ly/3LEzA4b.
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✨ The GeoPAT 2 software allows the segmentation/regionalization of large spatial raster data.✨
Now, thanks to D G Rossiter, it can now be installed on MacOS.
You can find all of the instructions and other links at https://buff.ly/3LEzA4b.
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🎆 I wrote a short paper inventorying existing methods for comparing spatial patterns in raster data and listing their #rstats implementations 🎆
Read it at https://buff.ly/3W214FC
Check examples at https://buff.ly/4cWhjLh
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🎆 I wrote a short paper inventorying existing methods for comparing spatial patterns in raster data and listing their #rstats implementations 🎆
Read it at https://buff.ly/3W214FC
Check examples at https://buff.ly/4cWhjLh
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🛝 At https://buff.ly/3W3uwLp you can find the slides from my talk about comparing spatial patterns in raster data from the #foss4ge2024 conference in Tartu, Estonia.🛝
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🛝 At https://buff.ly/3W3uwLp you can find the slides from my talk about comparing spatial patterns in raster data from the #foss4ge2024 conference in Tartu, Estonia.🛝
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My talk "Comparing spatial patterns in raster data using R" at #foss4ge2024 in Tartu:
📅 2024-07-04
🕥 10:30 local time (https://buff.ly/3zmUemm)
📺 Watch live: https://buff.ly/3VPTTAh -
My talk "Comparing spatial patterns in raster data using R" at #foss4ge2024 in Tartu:
📅 2024-07-04
🕥 10:30 local time (https://buff.ly/3zmUemm)
📺 Watch live: https://buff.ly/3VPTTAh -
🔥 Thrilled to receive the MSCA Fellowship for my project, PRISM🔥
Over the next two years, I'll be based at the University of Münster, collaborating with Hanna Meyer to incorporate understanding of spatial patterns into machine learning algorithms.
Looking forward to this experience (starting in August).
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🔥 Thrilled to receive the MSCA Fellowship for my project, PRISM🔥
Over the next two years, I'll be based at the University of Münster, collaborating with Hanna Meyer to incorporate understanding of spatial patterns into machine learning algorithms.
Looking forward to this experience (starting in August).
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❔ Do you know of any #rstats packages that can be used to compare two spatial rasters? Please let me know!❔
(I am working on a short paper on this topic -- I will share it in the future)
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❔ Do you know of any #rstats packages that can be used to compare two spatial rasters? Please let me know!❔
(I am working on a short paper on this topic -- I will share it in the future)
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Spatial patterns have been used for years to understand regime shifts in ecosystems - but not in coral reefs. Can spatial patterns predict regime shifts occurring in coral communities? Read this new article by Génin et al. ahead of print!
https://www.journals.uchicago.edu/doi/10.1086/728117#coralReefs #regimeShifts #spatialPatterns #ecosystem #coral
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Spatial patterns have been used for years to understand regime shifts in ecosystems - but not in coral reefs. Can spatial patterns predict regime shifts occurring in coral communities? Read this new article by Génin et al. ahead of print!
https://www.journals.uchicago.edu/doi/10.1086/728117#coralReefs #regimeShifts #spatialPatterns #ecosystem #coral
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🎆 The version of 2.1 of the landscapemetrics package is now on CRAN.🎆
It brings some bug fixes and many speed improvements.
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🎆 The version of 2.1 of the landscapemetrics package is now on CRAN.🎆
It brings some bug fixes and many speed improvements.
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My new blog post discusses the use of the motif R package to extract information about the composition and configuration of spatial patterns in categorical rasters.
Read it at https://jakubnowosad.com/posts/2023-11-18-motif-bp7/
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My new blog post discusses the use of the motif R package to extract information about the composition and configuration of spatial patterns in categorical rasters.
Read it at https://jakubnowosad.com/posts/2023-11-18-motif-bp7/
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My recent talk "Analysis of Spatial Patterns: Current State and Future Challenges" presented at IIASA explores methods for quantification and exploration of spatial patterns.
You can find the slides at https://jakubnowosad.com/iiasa2023/.
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My recent talk "Analysis of Spatial Patterns: Current State and Future Challenges" presented at IIASA explores methods for quantification and exploration of spatial patterns.
You can find the slides at https://jakubnowosad.com/iiasa2023/.
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Non-survival to pension age in Denmark and Sweden: a sub-national investigation
New preprint: https://osf.io/y9ke4
I construct full life tables for the small populations of 🇩🇰 municipalities, apply spatial clustering, and male survival at ages 50—65 to 🇸🇪
Look at Copenhagen!
#Demography #SmallArea #Municipalities #Survival #Inequality #SpatialPatterns #rstats #rspatial
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Non-survival to pension age in Denmark and Sweden: a sub-national investigation
New preprint: https://osf.io/y9ke4
I construct full life tables for the small populations of 🇩🇰 municipalities, apply spatial clustering, and male survival at ages 50—65 to 🇸🇪
Look at Copenhagen!
#Demography #SmallArea #Municipalities #Survival #Inequality #SpatialPatterns #rstats #rspatial
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{supercells}: Superpixels of Spatial Data
The supercells() function is the core of the {supercells} package. An overview of its arguments is available at https://jakubnowosad.com/supercells/articles/main-function.html.
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{supercells}: Superpixels of Spatial Data
The supercells() function is the core of the {supercells} package. An overview of its arguments is available at https://jakubnowosad.com/supercells/articles/main-function.html.